| Commit message (Collapse) | Author | Age | Files | Lines |
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## What changes were proposed in this pull request?
- Deprecate old Java accumulator API; should use Scala now
- Update Java tests and examples
- Don't bother testing old accumulator API in Java 8 (too)
- (fix a misspelling too)
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes #13606 from srowen/SPARK-15086.
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ML examples
## What changes were proposed in this pull request?
Since [SPARK-15617](https://issues.apache.org/jira/browse/SPARK-15617) deprecated ```precision``` in ```MulticlassClassificationEvaluator```, many ML examples broken.
```python
pyspark.sql.utils.IllegalArgumentException: u'MulticlassClassificationEvaluator_4c3bb1d73d8cc0cedae6 parameter metricName given invalid value precision.'
```
We should use ```accuracy``` to replace ```precision``` in these examples.
## How was this patch tested?
Offline tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #13519 from yanboliang/spark-15771.
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## What changes were proposed in this pull request?
See [SPARK-15605](https://issues.apache.org/jira/browse/SPARK-15605) for the detail of this bug. This PR fix 2 major bugs in this example:
* The java example class use Param ```maxIter```, it will fail when calling ```Param.shouldOwn```. We need add a public method which return the ```maxIter``` Object. Because ```Params.params``` use java reflection to list all public method whose return type is ```Param```, and invoke them to get all defined param objects in the instance.
* The ```uid``` member defined in Java class will be initialized after Scala traits such as ```HasFeaturesCol```. So when ```HasFeaturesCol``` being constructed, they get ```uid``` with null, which will cause ```Param.shouldOwn``` check fail.
so, here is my changes:
* Add public method:
```public IntParam getMaxIterParam() {return maxIter;}```
* Use Java anonymous class overriding ```uid()``` to defined the ```uid```, and it solve the second problem described above.
* To make the ```getMaxIterParam ``` can be invoked using java reflection, we must make the two class (MyJavaLogisticRegression and MyJavaLogisticRegressionModel) public. so I make them become inner public static class.
## How was this patch tested?
Offline tests.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #13353 from yanboliang/spark-15605.
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## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
In the MLLib naivebayes example, scala and python example doesn't use libsvm data, but Java does.
I make changes in scala and python example to use the libsvm data as the same as Java example.
## How was this patch tested?
Manual tests
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes #13301 from wangmiao1981/example.
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## What changes were proposed in this pull request?
`a` -> `an`
I use regex to generate potential error lines:
`grep -in ' a [aeiou]' mllib/src/main/scala/org/apache/spark/ml/*/*scala`
and review them line by line.
## How was this patch tested?
local build
`lint-java` checking
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #13317 from zhengruifeng/a_an.
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## What changes were proposed in this pull request?
Several classes and methods have been deprecated and are creating lots of build warnings in branch-2.0. This issue is to identify and fix those items:
* WithSGD classes: Change to make class not deprecated, object deprecated, and public class constructor deprecated. Any public use will require a deprecated API. We need to keep a non-deprecated private API since we cannot eliminate certain uses: Python API, streaming algs, and examples.
* Use in PythonMLlibAPI: Change to using private constructors
* Streaming algs: No warnings after we un-deprecate the classes
* Examples: Deprecate or change ones which use deprecated APIs
* MulticlassMetrics fields (precision, etc.)
* LinearRegressionSummary.model field
## How was this patch tested?
Existing tests. Checked for warnings manually.
Author: Sean Owen <sowen@cloudera.com>
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #13314 from jkbradley/warning-cleanups.
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## What changes were proposed in this pull request?
Use `SparkSession` according to [SPARK-15031](https://issues.apache.org/jira/browse/SPARK-15031)
`MLLLIB` is not recommended to use now, so examples in `MLLIB` are ignored in this PR.
`StreamingContext` can not be directly obtained from `SparkSession`, so example in `Streaming` are ignored too.
cc andrewor14
## How was this patch tested?
manual tests with spark-submit
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #13164 from zhengruifeng/use_sparksession_ii.
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## What changes were proposed in this pull request?
MLlib are not recommended to use, and some methods are even deprecated.
Update the warning message to recommend ML usage.
```
def showWarning() {
System.err.println(
"""WARN: This is a naive implementation of Logistic Regression and is given as an example!
|Please use either org.apache.spark.mllib.classification.LogisticRegressionWithSGD or
|org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
|for more conventional use.
""".stripMargin)
}
```
To
```
def showWarning() {
System.err.println(
"""WARN: This is a naive implementation of Logistic Regression and is given as an example!
|Please use org.apache.spark.ml.classification.LogisticRegression
|for more conventional use.
""".stripMargin)
}
```
## How was this patch tested?
local build
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #13190 from zhengruifeng/update_recd.
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## What changes were proposed in this pull request?
Refactor All Java Tests that use SparkSession, to extend SharedSparkSesion
## How was this patch tested?
Existing Tests
Author: Sandeep Singh <sandeep@techaddict.me>
Closes #13101 from techaddict/SPARK-15296.
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SparkSession
## What changes were proposed in this pull request?
It seems most of Python examples were changed to use SparkSession by https://github.com/apache/spark/pull/12809. This PR said both examples below:
- `simple_params_example.py`
- `aft_survival_regression.py`
are not changed because it dose not work. It seems `aft_survival_regression.py` is changed by https://github.com/apache/spark/pull/13050 but `simple_params_example.py` is not yet.
This PR corrects the example and make this use SparkSession.
In more detail, it seems `threshold` is replaced to `thresholds` here and there by https://github.com/apache/spark/commit/5a23213c148bfe362514f9c71f5273ebda0a848a. However, when it calls `lr.fit(training, paramMap)` this overwrites the values. So, `threshold` was 5 and `thresholds` becomes 5.5 (by `1 / (1 + thresholds(0) / thresholds(1)`).
According to the comment below. this is not allowed, https://github.com/apache/spark/blob/354f8f11bd4b20fa99bd67a98da3525fd3d75c81/mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala#L58-L61.
So, in this PR, it sets the equivalent value so that this does not throw an exception.
## How was this patch tested?
Manully (`mvn package -DskipTests && spark-submit simple_params_example.py`)
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #13135 from HyukjinKwon/SPARK-15031.
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dataset.registerTempTable
## What changes were proposed in this pull request?
Update the unit test code, examples, and documents to remove calls to deprecated method `dataset.registerTempTable`.
## How was this patch tested?
This PR only changes the unit test code, examples, and comments. It should be safe.
This is a follow up of PR https://github.com/apache/spark/pull/12945 which was merged.
Author: Sean Zhong <seanzhong@databricks.com>
Closes #13098 from clockfly/spark-15171-remove-deprecation.
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algorithms
## What changes were proposed in this pull request?
Once SPARK-14487 and SPARK-14549 are merged, we will migrate to use the new vector and matrix type in the new ml pipeline based apis.
## How was this patch tested?
Unit tests
Author: DB Tsai <dbt@netflix.com>
Author: Liang-Chi Hsieh <simonh@tw.ibm.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes #12627 from dbtsai/SPARK-14615-NewML.
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## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
Add guide doc and examples for GaussianMixture in Spark.ml in Java, Scala and Python.
## How was this patch tested?
(Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
Manual compile and test all examples
Author: wm624@hotmail.com <wm624@hotmail.com>
Closes #12788 from wangmiao1981/example.
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## What changes were proposed in this pull request?
Add Scala/Java/Python examples for ```GeneralizedLinearRegression```.
## How was this patch tested?
They are examples and have been tested offline.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes #12754 from yanboliang/spark-14979.
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## What changes were proposed in this pull request?
Deprecates registerTempTable and add dataset.createTempView, dataset.createOrReplaceTempView.
## How was this patch tested?
Unit tests.
Author: Sean Zhong <seanzhong@databricks.com>
Closes #12945 from clockfly/spark-15171.
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in examples
## What changes were proposed in this pull request?
1, Use `SparkSession` according to [SPARK-15031](https://issues.apache.org/jira/browse/SPARK-15031)
2, Update indent for `SparkContext` according to [SPARK-15134](https://issues.apache.org/jira/browse/SPARK-15134)
3, BTW, remove some duplicate space and add missing '.'
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #13050 from zhengruifeng/use_sparksession.
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## What changes were proposed in this pull request?
This fixes compile errors.
## How was this patch tested?
Pass the Jenkins tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #13053 from dongjoon-hyun/hotfix_sqlquerysuite.
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## What changes were proposed in this pull request?
1,create a libsvm-type dataset for lda: `data/mllib/sample_lda_libsvm_data.txt`
2,add python example
3,directly read the datafile in examples
4,BTW, change to `SparkSession` in `aft_survival_regression.py`
## How was this patch tested?
manual tests
`./bin/spark-submit examples/src/main/python/ml/lda_example.py`
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #12927 from zhengruifeng/lda_pe.
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## What changes were proposed in this pull request?
Python example for ml.kmeans already exists, but not included in user guide.
1,small changes like: `example_on` `example_off`
2,add it to user guide
3,update examples to directly read datafile
## How was this patch tested?
manual tests
`./bin/spark-submit examples/src/main/python/ml/kmeans_example.py
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #12925 from zhengruifeng/km_pe.
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ml.BisectingKMeans
## What changes were proposed in this pull request?
1, add BisectingKMeans to ml-clustering.md
2, add the missing Scala BisectingKMeansExample
3, create a new datafile `data/mllib/sample_kmeans_data.txt`
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #11844 from zhengruifeng/doc_bkm.
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## What changes were proposed in this pull request?
1, Add python example for OneVsRest
2, remove args-parsing
## How was this patch tested?
manual tests
`./bin/spark-submit examples/src/main/python/ml/one_vs_rest_example.py`
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #12920 from zhengruifeng/ovr_pe.
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This PR removes `sqlContext` in examples. Actual usage was all replaced in https://github.com/apache/spark/pull/12809 but there are some in comments.
Manual style checking.
Author: hyukjinkwon <gurwls223@gmail.com>
Closes #13006 from HyukjinKwon/minor-docs.
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Cleans up ALS examples by removing unnecessary casts to double for `rating` and `prediction` columns, since `RegressionEvaluator` now supports `Double` & `Float` input types.
## How was this patch tested?
Manual compile and run with `run-example ml.ALSExample` and `spark-submit examples/src/main/python/ml/als_example.py`.
Author: Nick Pentreath <nickp@za.ibm.com>
Closes #12892 from MLnick/als-examples-cleanup.
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binary_classification_metrics_example.py
## What changes were proposed in this pull request?
This issue addresses the comments in SPARK-15031 and also fix java-linter errors.
- Use multiline format in SparkSession builder patterns.
- Update `binary_classification_metrics_example.py` to use `SparkSession`.
- Fix Java Linter errors (in SPARK-13745, SPARK-15031, and so far)
## How was this patch tested?
After passing the Jenkins tests and run `dev/lint-java` manually.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #12911 from dongjoon-hyun/SPARK-15134.
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## What changes were proposed in this pull request?
This PR aims to update Scala/Python/Java examples by replacing `SQLContext` with newly added `SparkSession`.
- Use **SparkSession Builder Pattern** in 154(Scala 55, Java 52, Python 47) files.
- Add `getConf` in Python SparkContext class: `python/pyspark/context.py`
- Replace **SQLContext Singleton Pattern** with **SparkSession Singleton Pattern**:
- `SqlNetworkWordCount.scala`
- `JavaSqlNetworkWordCount.java`
- `sql_network_wordcount.py`
Now, `SQLContexts` are used only in R examples and the following two Python examples. The python examples are untouched in this PR since it already fails some unknown issue.
- `simple_params_example.py`
- `aft_survival_regression.py`
## How was this patch tested?
Manual.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #12809 from dongjoon-hyun/SPARK-15031.
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## What changes were proposed in this pull request?
Use Long.parseLong which returns a primative.
Use a series of appends() reduces the creation of an extra StringBuilder type
## How was this patch tested?
Unit tests
Author: Azeem Jiva <azeemj@gmail.com>
Closes #12520 from javawithjiva/minor.
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Double values; results in type Object
## What changes were proposed in this pull request?
Java `sampleByKey` methods should accept `Map` with `java.lang.Double` values
## How was this patch tested?
Existing (updated) Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes #12637 from srowen/SPARK-14873.
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non-declared InterruptedException
## What changes were proposed in this pull request?
`JavaStreamingContext.awaitTermination` methods should be declared as `throws[InterruptedException]` so that this exception can be handled in Java code. Note this is not just a doc change, but an API change, since now (in Java) the method has a checked exception to handle. All await-like methods in Java APIs behave this way, so seems worthwhile for 2.0.
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes #12418 from srowen/SPARK-8393.
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## What changes were proposed in this pull request?
Currently, the docs for TF-IDF only refer to using HashingTF with IDF. However, CountVectorizer can also be used. We should probably amend the user guide and examples to show this.
## How was this patch tested?
unit tests and doc generation
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #12454 from hhbyyh/tfdoc.
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jira: https://issues.apache.org/jira/browse/SPARK-13089
Add section in ml-classification.md for NaiveBayes DataFrame-based API, plus example code (using include_example to clip code from examples/ folder files).
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #11015 from hhbyyh/naiveBayesDoc.
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## What changes were proposed in this pull request?
Fixes to eliminate warnings during package and doc builds.
## How was this patch tested?
Existing unit tests
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #12263 from jkbradley/warning-cleanups.
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## What changes were proposed in this pull request?
This PR updates MLlib APIs to accept `Dataset[_]` as input where `DataFrame` was the input type. This PR doesn't change the output type. In Java, `Dataset[_]` maps to `Dataset<?>`, which includes `Dataset<Row>`. Some implementations were changed in order to return `DataFrame`. Tests and examples were updated. Note that this is a breaking change for subclasses of Transformer/Estimator.
Lol, we don't have to rename the input argument, which has been `dataset` since Spark 1.2.
TODOs:
- [x] update MiMaExcludes (seems all covered by explicit filters from SPARK-13920)
- [x] Python
- [x] add a new test to accept Dataset[LabeledPoint]
- [x] remove unused imports of Dataset
## How was this patch tested?
Exiting unit tests with some modifications.
cc: rxin jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes #12274 from mengxr/SPARK-14500.
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## What changes were proposed in this pull request?
This fix tries to remove duplicate Java code in examples/mllib and examples/ml. The following changes have been made:
```
deleted: ml/JavaCrossValidatorExample.java (duplicate of JavaModelSelectionViaCrossValidationExample.java)
deleted: ml/JavaTrainValidationSplitExample.java (duplicated of JavaModelSelectionViaTrainValidationSplitExample.java)
deleted: mllib/JavaFPGrowthExample.java (duplicate of JavaSimpleFPGrowth.java)
deleted: mllib/JavaLDAExample.java (duplicate of JavaLatentDirichletAllocationExample.java)
deleted: mllib/JavaKMeans.java (merged with JavaKMeansExample.java)
deleted: mllib/JavaLR.java (duplicate of JavaLinearRegressionWithSGDExample.java)
updated: mllib/JavaKMeansExample.java (merged with mllib/JavaKMeans.java)
```
## How was this patch tested?
Existing tests passed.
Author: Yong Tang <yong.tang.github@outlook.com>
Closes #12143 from yongtang/SPARK-14301.
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analysis results
## What changes were proposed in this pull request?
This PR contains the following 5 types of maintenance fix over 59 files (+94 lines, -93 lines).
- Fix typos(exception/log strings, testcase name, comments) in 44 lines.
- Fix lint-java errors (MaxLineLength) in 6 lines. (New codes after SPARK-14011)
- Use diamond operators in 40 lines. (New codes after SPARK-13702)
- Fix redundant semicolon in 5 lines.
- Rename class `InferSchemaSuite` to `CSVInferSchemaSuite` in CSVInferSchemaSuite.scala.
## How was this patch tested?
Manual and pass the Jenkins tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #12139 from dongjoon-hyun/SPARK-14355.
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## What changes were proposed in this pull request?
This PR fixes some newly added java-lint errors(unused-imports, line-lengsth).
## How was this patch tested?
Pass the Jenkins tests.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #11968 from dongjoon-hyun/SPARK-14167.
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## What changes were proposed in this pull request?
This PR moves flume back to Spark as per the discussion in the dev mail-list.
## How was this patch tested?
Existing Jenkins tests.
Author: Shixiong Zhu <shixiong@databricks.com>
Closes #11895 from zsxwing/move-flume-back.
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using include_example
Replace example code in mllib-feature-extraction.md using include_example
https://issues.apache.org/jira/browse/SPARK-13017
The example code in the user guide is embedded in the markdown and hence it is not easy to test. It would be nice to automatically test them. This JIRA is to discuss options to automate example code testing and see what we can do in Spark 1.6.
Goal is to move actual example code to spark/examples and test compilation in Jenkins builds. Then in the markdown, we can reference part of the code to show in the user guide. This requires adding a Jekyll tag that is similar to https://github.com/jekyll/jekyll/blob/master/lib/jekyll/tags/include.rb, e.g., called include_example.
`{% include_example scala/org/apache/spark/examples/mllib/TFIDFExample.scala %}`
Jekyll will find `examples/src/main/scala/org/apache/spark/examples/mllib/TFIDFExample.scala` and pick code blocks marked "example" and replace code block in
`{% highlight %}`
in the markdown.
See more sub-tasks in parent ticket: https://issues.apache.org/jira/browse/SPARK-11337
Author: Xin Ren <iamshrek@126.com>
Closes #11142 from keypointt/SPARK-13017.
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mllib-statistics.md using include_example
## What changes were proposed in this pull request?
This PR for ticket SPARK-13019 is based on previous PR(https://github.com/apache/spark/pull/11108).
Since PR(https://github.com/apache/spark/pull/11108) is breaking scala-2.10 build, more work is needed to fix build errors.
What I did new in this PR is adding keyword argument for 'fractions':
` val approxSample = data.sampleByKey(withReplacement = false, fractions = fractions)`
` val exactSample = data.sampleByKeyExact(withReplacement = false, fractions = fractions)`
I reopened ticket on JIRA but sorry I don't know how to reopen a GitHub pull request, so I just submitting a new pull request.
## How was this patch tested?
Manual build testing on local machine, build based on scala-2.10.
Author: Xin Ren <iamshrek@126.com>
Closes #11901 from keypointt/SPARK-13019.
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using include_example"
This reverts commit 1af8de200c4d3357bcb09e7bbc6deece00e885f2.
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include_example
https://issues.apache.org/jira/browse/SPARK-13019
The example code in the user guide is embedded in the markdown and hence it is not easy to test. It would be nice to automatically test them. This JIRA is to discuss options to automate example code testing and see what we can do in Spark 1.6.
Goal is to move actual example code to spark/examples and test compilation in Jenkins builds. Then in the markdown, we can reference part of the code to show in the user guide. This requires adding a Jekyll tag that is similar to https://github.com/jekyll/jekyll/blob/master/lib/jekyll/tags/include.rb, e.g., called include_example.
`{% include_example scala/org/apache/spark/examples/mllib/SummaryStatisticsExample.scala %}`
Jekyll will find `examples/src/main/scala/org/apache/spark/examples/mllib/SummaryStatisticsExample.scala` and pick code blocks marked "example" and replace code block in
`{% highlight %}`
in the markdown.
See more sub-tasks in parent ticket: https://issues.apache.org/jira/browse/SPARK-11337
Author: Xin Ren <iamshrek@126.com>
Closes #11108 from keypointt/SPARK-13019.
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## What changes were proposed in this pull request?
[Spark Coding Style Guide](https://cwiki.apache.org/confluence/display/SPARK/Spark+Code+Style+Guide) has 100-character limit on lines, but it's disabled for Java since 11/09/15. This PR enables **LineLength** checkstyle again. To help that, this also introduces **RedundantImport** and **RedundantModifier**, too. The following is the diff on `checkstyle.xml`.
```xml
- <!-- TODO: 11/09/15 disabled - the lengths are currently > 100 in many places -->
- <!--
<module name="LineLength">
<property name="max" value="100"/>
<property name="ignorePattern" value="^package.*|^import.*|a href|href|http://|https://|ftp://"/>
</module>
- -->
<module name="NoLineWrap"/>
<module name="EmptyBlock">
<property name="option" value="TEXT"/>
-167,5 +164,7
</module>
<module name="CommentsIndentation"/>
<module name="UnusedImports"/>
+ <module name="RedundantImport"/>
+ <module name="RedundantModifier"/>
```
## How was this patch tested?
Currently, `lint-java` is disabled in Jenkins. It needs a manual test.
After passing the Jenkins tests, `dev/lint-java` should passes locally.
Author: Dongjoon Hyun <dongjoon@apache.org>
Closes #11831 from dongjoon-hyun/SPARK-14011.
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## What changes were proposed in this pull request?
Fix some nits discussed in https://github.com/apache/spark/pull/11776#issuecomment-198207419
use !rdd.isEmpty instead of rdd.count > 0
use static instead of AtomicInteger
remove unneeded "throws Exception"
## How was this patch tested?
manual tests
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #11821 from zhengruifeng/je_fix.
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## What changes were proposed in this pull request?
Add the java example of StreamingTest
## How was this patch tested?
manual tests in CLI: bin/run-example mllib.JavaStreamingTestExample dataDir 5 100
Author: Zheng RuiFeng <ruifengz@foxmail.com>
Closes #11776 from zhengruifeng/streaming_je.
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streaming-zeromq, streaming-akka, streaming-twitter to Spark packages
## What changes were proposed in this pull request?
Currently there are a few sub-projects, each for integrating with different external sources for Streaming. Now that we have better ability to include external libraries (spark packages) and with Spark 2.0 coming up, we can move the following projects out of Spark to https://github.com/spark-packages
- streaming-flume
- streaming-akka
- streaming-mqtt
- streaming-zeromq
- streaming-twitter
They are just some ancillary packages and considering the overhead of maintenance, running tests and PR failures, it's better to maintain them out of Spark. In addition, these projects can have their different release cycles and we can release them faster.
I have already copied these projects to https://github.com/spark-packages
## How was this patch tested?
Jenkins tests
Author: Shixiong Zhu <shixiong@databricks.com>
Closes #11672 from zsxwing/remove-external-pkg.
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byte[] conversions (and remaining Coverity items)
## What changes were proposed in this pull request?
- Fixes calls to `new String(byte[])` or `String.getBytes()` that rely on platform default encoding, to use UTF-8
- Same for `InputStreamReader` and `OutputStreamWriter` constructors
- Standardizes on UTF-8 everywhere
- Standardizes specifying the encoding with `StandardCharsets.UTF-8`, not the Guava constant or "UTF-8" (which means handling `UnuspportedEncodingException`)
- (also addresses the other remaining Coverity scan issues, which are pretty trivial; these are separated into commit https://github.com/srowen/spark/commit/1deecd8d9ca986d8adb1a42d315890ce5349d29c )
## How was this patch tested?
Jenkins tests
Author: Sean Owen <sowen@cloudera.com>
Closes #11657 from srowen/SPARK-13823.
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## What changes were proposed in this pull request?
This PR removes two methods, `collectRows()` and `takeRows()`, from `Dataset[T]`. These methods were added in PR #11443, and were later considered not useful.
## How was this patch tested?
Existing tests should do the work.
Author: Cheng Lian <lian@databricks.com>
Closes #11678 from liancheng/remove-collect-rows-and-take-rows.
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## What changes were proposed in this pull request?
PR #11443 temporarily disabled MiMA check, this PR re-enables it.
One extra change is that `object DataFrame` is also removed. The only purpose of introducing `object DataFrame` was to use it as an internal factory for creating `Dataset[Row]`. By replacing this internal factory with `Dataset.newDataFrame`, both `DataFrame` and `DataFrame$` are entirely removed from the API, so that we can simply put a `MissingClassProblem` filter in `MimaExcludes.scala` for most DataFrame API changes.
## How was this patch tested?
Tested by MiMA check triggered by Jenkins.
Author: Cheng Lian <lian@databricks.com>
Closes #11656 from liancheng/re-enable-mima.
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MaxAbsScaler example
## What changes were proposed in this pull request?
Fix build failure introduced in #11392 (change `DataFrame` -> `Dataset<Row>`).
## How was this patch tested?
Existing build/unit tests
Author: Nick Pentreath <nick.pentreath@gmail.com>
Closes #11653 from MLnick/java-maxabs-example-fix.
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## What changes were proposed in this pull request?
jira: https://issues.apache.org/jira/browse/SPARK-13512
Add example and doc for ml.feature.MaxAbsScaler.
## How was this patch tested?
unit tests
Author: Yuhao Yang <hhbyyh@gmail.com>
Closes #11392 from hhbyyh/maxabsdoc.
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## What changes were proposed in this pull request?
This PR unifies DataFrame and Dataset by migrating existing DataFrame operations to Dataset and make `DataFrame` a type alias of `Dataset[Row]`.
Most Scala code changes are source compatible, but Java API is broken as Java knows nothing about Scala type alias (mostly replacing `DataFrame` with `Dataset<Row>`).
There are several noticeable API changes related to those returning arrays:
1. `collect`/`take`
- Old APIs in class `DataFrame`:
```scala
def collect(): Array[Row]
def take(n: Int): Array[Row]
```
- New APIs in class `Dataset[T]`:
```scala
def collect(): Array[T]
def take(n: Int): Array[T]
def collectRows(): Array[Row]
def takeRows(n: Int): Array[Row]
```
Two specialized methods `collectRows` and `takeRows` are added because Java doesn't support returning generic arrays. Thus, for example, `DataFrame.collect(): Array[T]` actually returns `Object` instead of `Array<T>` from Java side.
Normally, Java users may fall back to `collectAsList` and `takeAsList`. The two new specialized versions are added to avoid performance regression in ML related code (but maybe I'm wrong and they are not necessary here).
1. `randomSplit`
- Old APIs in class `DataFrame`:
```scala
def randomSplit(weights: Array[Double], seed: Long): Array[DataFrame]
def randomSplit(weights: Array[Double]): Array[DataFrame]
```
- New APIs in class `Dataset[T]`:
```scala
def randomSplit(weights: Array[Double], seed: Long): Array[Dataset[T]]
def randomSplit(weights: Array[Double]): Array[Dataset[T]]
```
Similar problem as above, but hasn't been addressed for Java API yet. We can probably add `randomSplitAsList` to fix this one.
1. `groupBy`
Some original `DataFrame.groupBy` methods have conflicting signature with original `Dataset.groupBy` methods. To distinguish these two, typed `Dataset.groupBy` methods are renamed to `groupByKey`.
Other noticeable changes:
1. Dataset always do eager analysis now
We used to support disabling DataFrame eager analysis to help reporting partially analyzed malformed logical plan on analysis failure. However, Dataset encoders requires eager analysi during Dataset construction. To preserve the error reporting feature, `AnalysisException` now takes an extra `Option[LogicalPlan]` argument to hold the partially analyzed plan, so that we can check the plan tree when reporting test failures. This plan is passed by `QueryExecution.assertAnalyzed`.
## How was this patch tested?
Existing tests do the work.
## TODO
- [ ] Fix all tests
- [ ] Re-enable MiMA check
- [ ] Update ScalaDoc (`since`, `group`, and example code)
Author: Cheng Lian <lian@databricks.com>
Author: Yin Huai <yhuai@databricks.com>
Author: Wenchen Fan <wenchen@databricks.com>
Author: Cheng Lian <liancheng@users.noreply.github.com>
Closes #11443 from liancheng/ds-to-df.
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